add app files

app.py

@@ -3,6 +3,7 @@ import gradio as gr
 import subprocess
 import uuid
 import shutil
+import psutil
 from huggingface_hub import snapshot_download
 
 # ----------------------------------------
@@ -21,6 +22,15 @@ if not os.path.exists(MODEL_PATH) or len(os.listdir(MODEL_PATH)) == 0:
     )
     print("✅ Download complete.")
 
+    print("\n📂 Directory structure after download:")
+    for root, dirs, files in os.walk(MODEL_PATH):
+        level = root.replace(MODEL_PATH, "").count(os.sep)
+        indent = "    " * level
+        print(f"{indent}📁 {os.path.basename(root) or 'DOVE'}/")
+        subindent = "    " * (level + 1)
+        for f in sorted(files):
+            print(f"{subindent}📄 {f}")
+
 def list_downloaded_files(model_path):
     lines = []
     for root, dirs, files in os.walk(model_path):
@@ -31,8 +41,6 @@ def list_downloaded_files(model_path):
         for f in sorted(files):
             lines.append(f"{subindent}📄 {f}")
     return "\n".join(lines)
-file_tree = list_downloaded_files(MODEL_PATH)
-gr.Textbox(value=file_tree, label="Downloaded Files Tree", lines=20)
 
 # ----------------------------------------
 # Step 2: Setup Directories
@@ -52,7 +60,6 @@ def run_inference(video_path, save_format):
     input_path = os.path.join(UPLOAD_DIR, input_name)
     shutil.copy(video_path, input_path)
 
-    # --- Run inference script ---
     cmd = [
         "python", INFERENCE_SCRIPT,
         "--input_dir", UPLOAD_DIR,
@@ -64,10 +71,7 @@ def run_inference(video_path, save_format):
 
     try:
         inference_result = subprocess.run(
-            cmd,
-            capture_output=True,
-            text=True,
-            check=True
+            cmd, capture_output=True, text=True, check=True
         )
         print("📄 Inference stdout:\n", inference_result.stdout)
         print("⚠️ Inference stderr:\n", inference_result.stderr)
@@ -77,7 +81,6 @@ def run_inference(video_path, save_format):
         print("⚠️ STDERR:\n", e.stderr)
         return f"Inference failed:\n{e.stderr}", None
 
-    # --- Convert .mkv to .mp4 ---
     mkv_path = os.path.join(OUTPUT_DIR, input_name).replace(".mp4", ".mkv")
     mp4_path = os.path.join(OUTPUT_DIR, input_name)
 
@@ -87,10 +90,7 @@ def run_inference(video_path, save_format):
         ]
         try:
             convert_result = subprocess.run(
-                convert_cmd,
-                capture_output=True,
-                text=True,
-                check=True
+                convert_cmd, capture_output=True, text=True, check=True
             )
             print("🔄 FFmpeg stdout:\n", convert_result.stdout)
             print("⚠️ FFmpeg stderr:\n", convert_result.stderr)
@@ -106,11 +106,32 @@ def run_inference(video_path, save_format):
         return "Output video not found.", None
 
 # ----------------------------------------
-# Step 4: Gradio Interface
+# Step 4: System Resource Functions
+# ----------------------------------------
+def get_resources():
+    ram = psutil.virtual_memory().used / (1024**3)
+    disk = shutil.disk_usage('/').used / (1024**3)
+    total_disk = shutil.disk_usage('/').total / (1024**3)
+    cpu = psutil.cpu_percent()
+    return (
+        f"🧠 RAM Used: {ram:.2f} GB\n"
+        f"📀 Disk Used: {disk:.2f} GB / {total_disk:.2f} GB\n"
+        f"🖥️ CPU Usage: {cpu:.2f}%"
+    )
+
+def get_gpu_info():
+    try:
+        result = subprocess.run(["nvidia-smi"], capture_output=True, text=True, check=True)
+        return result.stdout
+    except Exception as e:
+        return "❌ GPU not available or error:\n" + str(e)
+
+# ----------------------------------------
+# Step 5: Gradio UI
 # ----------------------------------------
 with gr.Blocks() as demo:
-    gr.Markdown("# 🎥 DOVE Video SR + Restoration Inference Demo")
-    gr.Markdown("⚙️ **Note:** Default `save_format` is `yuv444p`. If playback fails, try `yuv420p` for compatibility.")
+    gr.Markdown("# 🎥 DOVE Video Super-Resolution & Restoration Demo")
+    gr.Markdown("⚙️ **Tip:** Default save format is `yuv444p`. If playback fails, try `yuv420p`.")
 
     with gr.Row():
         input_video = gr.Video(label="Upload input video")
@@ -120,7 +141,7 @@ with gr.Blocks() as demo:
         save_format = gr.Dropdown(
             choices=["yuv444p", "yuv420p"],
             value="yuv444p",
-            label="Save format (for video playback compatibility)"
+            label="Save format"
         )
 
     run_button = gr.Button("Run Inference")
@@ -132,4 +153,19 @@ with gr.Blocks() as demo:
         outputs=[status, output_video],
     )
 
+    gr.Markdown("## 🧾 Downloaded Model Files")
+    gr.Textbox(value=list_downloaded_files(MODEL_PATH), label="Model Directory Tree", lines=20)
+
+    gr.Markdown("## 🧠 System Resources")
+
+    with gr.Row():
+        res_btn = gr.Button("Check CPU/RAM/Disk")
+        gpu_btn = gr.Button("Check GPU (if available)")
+
+    sys_info = gr.Textbox(label="CPU, RAM, Disk")
+    gpu_info = gr.Textbox(label="GPU Info", lines=10)
+
+    res_btn.click(fn=get_resources, inputs=[], outputs=sys_info)
+    gpu_btn.click(fn=get_gpu_info, inputs=[], outputs=gpu_info)
+
 demo.launch()